Let's start by organizing the data into a frequency distribution. The last digits of the heights given are:

• $0: 9$ occurrences
• $1: 1$ occurrence
• $2: 2$ occurrences
• $3: 2$ occurrences
• $4: 2$ occurrences
• $5: 10$ occurrences
• $6: 1$ occurrence
• $7: 0$ occurrences
• $8: 3$ occurrences
• $9: 1$ occurrence

Now, let's complete the frequency distribution table:

Analysis:

1. Reporting or Measuring:

   • The digit "0" occurs disproportionately often, and "5" also has a high frequency. These digits are often used when people round numbers. Additionally, "7" never occurs, which is unusual if the data were truly measured.
   • Conclusion: The heights appear to be reported rather than actually measured.

2. Accuracy:

   • Since people often round to the nearest 0 or 5, the distribution suggests that the measurements might not be very accurate. Instead of precise measurements, these numbers might reflect estimates or rounded figures.

Questions to Consider:

1. How would the frequency distribution change if the data were measured more accurately?
2. What statistical tests can confirm if the data are rounded or actually measured?
3. How does the rounding of data affect statistical analysis outcomes?
4. What is the impact of biased data on the validity of research conclusions?
5. Can you identify other patterns in reported vs. measured data?

Tip:

When collecting data, it's crucial to ensure accuracy and precision to avoid introducing bias that can affect the outcome of statistical analysis.